Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research

Abstract

Tommaso Costa,1,2 Mario Ferraro,1– 3 Jordi Manuello,1,2 Alessia Camasio,2,3 Andrea Nani,2 Lorenzo Mancuso,2 Franco Cauda,1,2 Peter T Fox,4,5 Donato Liloia1,2 1GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; 2FOCUS Laboratory, Department of Psychology, University of Turin, Turin, Italy; 3Department of Physics, University of Turin, Turin, Italy; 4Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; 5Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USACorrespondence: Jordi Manuello, FOCUS Laboratory, Department of Psychology, University of Turin, Via Giuseppe Verdi 10, Turin, 10124, Italy, Email [email protected]: Over the past two decades, functional magnetic resonance imaging (fMRI) has become the primary tool for exploring neural correlates of emotion. To enhance the reliability of results in understanding the complex nature of emotional experiences, researchers combine findings from multiple fMRI studies using coordinate-based meta-analysis (CBMA). As one of the most widely employed CBMA methods worldwide, activation likelihood estimation (ALE) is of great importance in affective neuroscience and neuropsychology. This comprehensive review provides an introductory guide for implementing the ALE method in emotion research, outlining the experimental steps involved. By presenting a case study about the emotion of disgust, with regard to both its core and social processing, we offer insightful commentary as to how ALE can enable researchers to produce consistent results and, consequently, fruitfully investigate the neural mechanisms underpinning emotions, facilitating further progress in this field.Keywords: affective mapping, BrainMap, quantitative synthesis, coordinate-based meta-analysis, fMRI, affective neuroscience

Keywords

• affective mapping
• brainmap
• quantitative synthesis
• coordinate-based meta-analysis
• fmri
• affective neuroscience